1. Field of the Invention
The present invention relates to a system for real-time stereo matching, and more particularly, to a system for stereo matching which provides improved stereo matching speed and matching rate by gradually optimizing a disparity range for stereo matching using a stereo matching result of a previous frame image and thus reducing unnecessary computations for matching.
2. Description of the Related Art
Stereo matching is the technique that is used to acquire 3-dimensional information from two or more 2-dimensional images acquired from different locations at the same time, and relates to a series of correspondence problems for finding points corresponding to the same location of the two images (i.e., left/right images) and acquiring disparity information between the two corresponding points to thus acquire 3D depth information.
Solutions to the correspondence problems are mainly categorized into a feature-based matching and an area-based matching. The feature-based matching conducts matching at specific regions such as vertex or borders, but is unable to provide information about the rest regions other than the specific regions. The area-based matching finds corresponding points of the entire image by measuring internal correlativity of a predetermined size of window on the same parallel line of the left/right images, and thus provides dense 3D information.
FIG. 1 illustrates a conventional area-based matching which uses a predetermined window size and a predetermined disparity range. Referring to an example illustrated in FIG. 1, the point of the highest correlativity is found within a range between points B and B′, which is a predetermined disparity range, to find a corresponding location in the right image to the location A of the left image. In another example, the point of the highest correlativity is found within a predetermined disparity range between points D and D′ to find a corresponding location in the right image with respect to location C. Various methods including sum of absolute difference (SAD), sum of squared difference (SSD), normalized correlation (NCC) and census transform are employed to measure internal correlation of the predetermined window areas within the left/right images. However, because these schemes have to measure the correlativity across the entire region of the image, the computational cost to find the corresponding location rapidly increases as the disparity range to measure the correlativity along the same parallel lines of the left/right images increases, and also more time is consumed to acquire 3D information.
The conventional area-based stereo matching thus employs a way of removing redundant computations during measuring of internal correlativity in the window region and a way of predicting a disparity range of the search region to measure correlativity, to reduce need for computation and time for matching.